dplyrDplyr: A grammar of data manipulation

dplyr

Overview

dplyr is a grammar of data manipulation, providing a consistent set of
verbs that help you solve the most common data manipulation challenges:

mutate() adds new variables that are functions of existing
variables

select() picks variables based on their names.

filter() picks cases based on their values.

summarise() reduces multiple values down to a single summary.

arrange() changes the ordering of the rows.

These all combine naturally with group_by() which allows you to
perform any operation “by group”. You can learn more about them in
vignette("dplyr"). As well as these single-table verbs, dplyr also
provides a variety of two-table verbs, which you can learn about in
vignette("two-table").

dplyr is designed to abstract over how the data is stored. That means as
well as working with local data frames, you can also work with remote
database tables, using exactly the same R code. Install the dbplyr
package then read vignette("databases", package = "dbplyr").

If you are new to dplyr, the best place to start is the data import
chapter in R for data science.

Installation

# The easiest way to get dplyr is to install the whole tidyverse:
install.packages("tidyverse")
# Alternatively, install just dplyr:
install.packages("dplyr")

Development version

To get a bug fix, or use a feature from the development version, you can
install dplyr from GitHub.